H-field imager for assays

ABSTRACT

This disclosure describes a magnetic-field image sensor and method of use. In accordance with implementations of the magnetic-field image sensor, a sample can be placed on top of the magnetic field image sensor. An image of the magnetic nanoparticles or superparamagnetic nanoparticles can be created immediately afterwards based upon detection of a change in magnetic field caused by the magnetic nanoparticles or superparamagnetic nanoparticles. From this image, computer imaging algorithms can determine attributes (e.g., size, shape, type, quantity, distribution, etc.) of the target entity.

The present application is a Divisional of U.S. patent application Ser.No. 16/836,630, filed Mar. 31, 2020, and titled “H-FIELD IMAGER FORASSAYS”, which is a Divisional of U.S. patent application Ser. No.14/972,857 (issued as U.S. Pat. No. 10,605,816), filed Dec. 17, 2015 andtitled “H-FIELD IMAGER FOR ASSAYS”, which claims Priority fromProvisional Application No. 62/203,637, filed Aug. 11, 2015.

BACKGROUND

Assays are important for diagnosis because they can indicate bacterialinfections, viral infections, poisoning, overdose, and so forth. Mostassays have to be done in a laboratory and cannot be done in the home,where patients can benefit from the convenience and the privacy. To beeffective in Third World countries where medical doctors andlaboratories are scarce, the assays need to be done anywhere andanytime. Similarly, in times of disaster or in a war zone, the samemobile requirements must be met.

The reason that most assays cannot be mobile is that stationary machinesperform the analysis. These machines can be cabinet size down to benchtop size. They are expensive and need AC wall power. The technology inthe machines (e.g., flow cytometry, polymerase chain reaction,immunoassays, etc.) is poorly suited to be converted into a mobileimplementation.

In recent years, mobile assays have been developed to detect influenzaand Human Immunodeficiency Virus (HIV). These tests are qualitative andcannot provide a quantitative measurement of the entity in question. Forexample, the therapy for a human with HIV is based upon itsconcentration.

SUMMARY

This disclosure describes a magnetic-field image sensor and method ofuse. In accordance with implementations of the magnetic-field imagesensor, sample including functionalized magnetic nanoparticles (e.g.,mixed with functionalized magnetic nanoparticles) can be placed on topof a magnetic-field image sensor. An image of the magnetic nanoparticlescan be created immediately afterwards based upon detection of a changein magnetic field caused by the magnetic nanoparticles. From this image,computer imaging algorithms can determine attributes (e.g., size, shape,type, quantity, distribution, etc.) of cells, viruses, and otherentities.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

DRAWINGS

The Detailed Description is described with reference to the accompanyingfigures. The use of the same reference numbers in different instances inthe description and the figures may indicate similar or identical items.

FIGS. 1 through 4B are diagrammatic views of a magnetic-field imagesensor implemented in accordance with embodiments of the presentdisclosure.

FIG. 5 is flow diagram illustrating a method of imaging magneticnanoparticles or superparamagnetic nanoparticles in a fluid sample witha magnetic-field image sensor in accordance with present disclosure.

DETAILED DESCRIPTION Overview

A pixel-based image sensor is disclosed in which respective pixels of anarray of pixels senses changes in the magnetic field above therespective pixel to determine the presence and amount of magneticnanoparticles or superparamagnetic nanoparticles. From this information,attributes, such as size, type, morphology, distribution, number of thetarget entity can be deduced. In embodiments, the pitch of the pixelscan vary from 40 nm to 100 μm. Each pixel can be configured to detect achange in magnetic field proximate to the respective pixel. In someembodiments, the sensor is implemented as an integrated circuit. Thesensor can also be formed from patterned or printed conductors on asubstrate such as glass or plastic, where at least one integratedcircuit electrically connected to the pixels can be configured tomeasure the change in magnetic field. The magnetic-field image sensor iswell suited to be implemented in a mobile test because it is small, lowpower, low cost, and disposable. For example, the resulting mobiledetection or measurement device that includes a magnetic field imagesensor may have dimensions that range from about four centimeters (4 cm)by about two centimeters (2 cm) by about one millimeter (1 mm) to abouttwenty centimeters (20 cm) by about five centimeters (5 cm) by about onecentimeter (1 cm). Thus, the magnetic-field image sensor can be utilizedin a number of environmental settings. For instance, the magnetic-fieldimage sensor may be utilized in an indoor environment, in a hostileenvironment, in an outdoors environment, or the like.

Example Implementations

FIG. 1 illustrates a magnetic-field (H-Field) image sensor 100 inaccordance with various embodiments of this disclosure. Those skilled inthe art will appreciate that the embodiments illustrated in the drawingsand/or described herein may be fully or partially combined to result inadditional embodiments. Accordingly, the illustrated and describedembodiments should be understood as explanatory and not as limitationsof the present disclosure.

In an embodiment illustrated in FIG. 1 , a magnetic field image sensor100 is shown to include a plurality of coils 102 (e.g., an array ofcoils deployed through the magnetic field image sensor 100) fordetecting changes in magnetic fields. Each coil 102 can define a pixelwithin the magnetic field image sensor 100. For instance, the array ofcoils 102 defines an active sensor area where a fluid sample includingcells, viruses, and other entities can be deposited over such thatrespective coils 102 can detect a change in the magnetic field caused bymagnetic nanoparticles or superparamagnetic nanoparticles. In one ormore implementations, the pitch between respective coils 102 can varyfrom 40 nanometers to 100 micrometers.

In embodiments, the image sensor 100 includes a layer 104. The layer 104is utilized to physically separate the cells, viruses, and otherentities from the coils 102. In implementations, the layer 104 comprisesany suitable material (e.g., an integrated circuit passivation layer,glass panel, or plastic substrate) that allows the coils 102 to detect achange in magnetic field caused by magnetic nanoparticles orsuperparamagnetic nanoparticles.

As shown in FIG. 1 , the image sensor 100 includes a primary excitationcoil 106 disposed about the panel 104. The primary excitation coil 106causes generation of a magnetic field that is perpendicular to a planedefined by the panel 104 when current flows through the primaryexcitation coil 106. If magnetic nanoparticles are in the sample, thenthey will rotate such that their magnetic moments will be alignedparallel to the magnetic field. If superparamagnetic nanoparticles arein the sample, then the magnetic field generated by the primaryexcitation coil 106 induces magnetism in the superparamagneticnanoparticles, which align their resulting magnetic moments parallel tothe magnetic field. In addition, the magnetic field interacts with themagnetic moment of the magnetic nanoparticles or the superparamagneticnanoparticles and pulls them to the plane of the magnetic field imagesensor.

In the embodiment shown in FIG. 2 , the magnetic field image sensor isused to count the number of cells 110 in a sample. The target cellsmight be infectious bacteria in whole human blood. Super paramagneticnanoparticles functionalized with antibodies 112 that bind to structureson the target cell can be mixed into the sample. The super paramagneticnanoparticles attach to the target cells. Once the primary excitationcoil 106 is turned on, then the super paramagnetic nanoparticles alignthemselves to the primary magnetic field. The nanoparticles are pulledto the image sensor, which senses the presence and amount ofnanoparticles on a pixel-by-pixel basis. Target cells have a much highernumber of nanoparticles attached to it than can be found elsewhere inthe sample. Suitable algorithms can interpret the resulting image frameto determine the number of cells for a given sample volume.

Referring to FIGS. 3A and 3B, in an agglutination assay, beads that arecovered with superparamagnetic nanoparticles functionalized with agentsthat have an affinity for the target entity are mixed into the sample.

If the target entity is present in the sample, then the beads clumptogether at a rate dependent upon the concentration of the target entityin the sample. As shown in FIG. 3B, clumps 108 of beads may extend overportions of one or more coils 102 (e.g., pixels). In one or moreimplementations, one or more coils 102 detect a change in the magneticfield as a result of the clumps 108 being directly disposed over therespective coils 102. For example, adjacent coils 102 may detect achange in a magnetic field due to a clump 108 being located directlyover the adjacent coils indicating the presence and the density ofsuperparamagnetic nanoparticles. For example, the image sensor 100 maydetermine a presence and density of superparamagnetic nanoparticlesbased upon the number of adjacent coils 102 detecting a change inmagnetic field due to the location of the clumps 108 with respect to theadjacent coils 102.

In another implementation of a coagulation assay, as shown in FIGS. 4Aand 4B, a biological sample, such as a blood sample, may be disposedover the panel 104 of the image sensor 100. In this implementation,superparamagnetic cylinders 202 can be added to the biological sample.An external magnetic field that is parallel to a plane defined by thepanel 104 can be generated that causes the superparamagnetic cylinders202 to align parallel with respect to the surface of the panel 104. Inone or more implementations, one or more attributes of the biologicalsample can be determined. For example, a coagulation measurement of thebiological can be determined by terminating the external magnetic fieldand causing current to flow through the primary excitation coil 106,which causes generation of a magnetic field that is perpendicular to thesurface of the panel 104. The magnetic field perpendicular to thesurface of the panel 104 causes the superparamagnetic cylinders 202 totransition from at least substantially parallel with respect to thesurface of the panel 104 to at least substantially perpendicular withrespect to the surface of the panel 104. One or more coils 102 detectthe changes in magnetic field as the super paramagnetic cylinder rotatesfrom parallel to perpendicular with respect to the surface of the panel104. In one or more implementations, the image sensor 100 measures atime ranging from the termination of the external magnetic field to thedetecting a presence of the superparamagnetic cylinder 202 due to itbeing at least substantially perpendicular to the surface of the panel104. Based upon the measured time, the image sensor 100 can determine acoagulation characteristic of the biological sample.

The image sensor 100 may further include processing logic embodied by aprogrammable logic device, a controller/microcontroller, a single ormultiple core processor, an ASIC, or the like. The processing logic maybe configured to generate an image based on changes in the magneticfield detected by one or more coils 102. In embodiments, the processinglogic can include fast Fourier transform (FFT) and magnetic fielddetection algorithms. The processing logic can further include one ormore computer imaging software modules executable by aprocessor/controller to identify attributes of cells/particles (e.g.,superparamagnetic nanoparticles) in the generated magnetic-field image.For example, the computer imaging modules may cause theprocessor/controller to perform a comparison between one or moreportions of the generated magnetic-field image and a library with storedimages or data associated with one or more attributes, such as size,type, morphology, distribution, number of cells, and so forth.

In some embodiments, the image sensor 100 can be configured to collectmultiple magnetic-field images taken at different times (e.g., timelapsed images) to monitor growth or movement of superparamagneticnanoparticles (or magnetic nanoparticles). For example, time lapsedimages from an agglutination assay can be used to monitor movement ofdispersed particles (e.g., antibody-coated beads) as they agglutinate inthe presence of an antigen.

In various embodiments of the present disclosure, the image sensor 100may be at least partially powered by a near-field communications (NFC)device. For instance, a mobile electronic device (e.g., a smart phone)having NFC technology may be positioned proximate to the image sensor100. Due to the proximity to the NFC technology of the mobile electronicdevice, the image sensor 100 may be at least partially powered by theNFC technology.

Example Processes

FIG. 5 shows a flow diagram for a method 300 of imaging biological cellsor viruses with a magnetic-field image sensor, such as the image sensor100 described herein. Accordingly, the method 300 may include any stepsor operations that are described herein with regard to themagnetic-field image sensor 100 or that are necessary for achieving anattribute of the magnetic-field image sensor 100 that is describedherein. However, the method 300 is in no way limited to any embodimentof the magnetic-field image sensor 100 described herein.

As shown in FIG. 5 , the method 300 can include: placing a sample on apanel disposed over a plurality of coils (e.g., image sensor 100), thesample including a fluid containing a target entity and functionalizedsuper paramagnetic nanoparticles with an agent that has an affinity forthe target entity (Block 302); generating an image based upon detectionof a change in magnetic field due to the super paramagneticnanoparticles (or paramagnetic nanoparticles) proximity to one or morecoils (Block 304); and determining one or more attributes of the targetentity based upon the generated image (Block 306). In someimplementations, determining the one or more attributes of the targetentity based upon the generated image can include performance of acomparison between one or more portions of the generated image with alibrary of stored images or data structures. For example, computerimaging algorithms may be executed by one or more processors to performcomparisons with a library of stored images or parameters to determineattributes of the target entity including one or more of: size, type,morphology, distribution, immunoassay characteristics, or number ofcells.

In some implementations, the magnetic-based sensor can include multipleactive sensor areas or regions (e.g., as discussed above with regard toimage sensor 100) with different respective sensor pitches suitable fordetecting differently sized particles (or different ranges of particlessizes). The method can further include as step of selecting a firstsensor area or a second sensor area based upon a size of a virus or cellbeing imaged.

Those skilled in the art will appreciate that the forgoing steps can becarried out in any order, unless otherwise indicated herein, and thatone or more steps may be carried out substantially simultaneously or atleast partially in parallel. It should be further recognized that thevarious functions, operations, blocks, or steps described throughout thepresent disclosure may be carried out by any combination of hardware,software, or firmware. Various steps or operations may be carried out byone or more of the following: electronic circuitry, logic gates,multiplexers, a programmable logic device, an application-specificintegrated circuit (ASIC), a controller/microcontroller, or a computingsystem. A computing system may include, but is not limited to, apersonal computing system, mainframe computing system, workstation,image computer, parallel processor, the cloud, or any other suitabledevice. In general, the terms “controller” and “computing system” arebroadly defined to encompass any device having one or more processors,which execute instructions from a carrier medium.

Program instructions implementing methods, such as those manifested byembodiments described herein, may be transmitted over or stored oncarrier medium. The carrier medium may be a transmission medium, suchas, but not limited to, a wire, cable, or wireless transmission link.The carrier medium may also include a non-transitory signal bearingmedium or storage medium such as, but not limited to, a read-onlymemory, a random access memory, a magnetic or optical disk, asolid-state or flash memory device, or a magnetic tape.

It is further contemplated that any embodiment of the disclosuremanifested above as a system or method may include at least a portion ofany other embodiment described herein. Those having skill in the artwill appreciate that there are various embodiments by which systems andmethods described herein can be implemented, and that the implementationwill vary with the context in which an embodiment of the disclosure isdeployed.

Furthermore, it is to be understood that the invention is defined by theappended claims. Although embodiments of this invention have beenillustrated, it is apparent that various modifications may be made bythose skilled in the art without departing from the scope and spirit ofthe disclosure.

What is claimed is:
 1. An image sensor comprising: a planar panel; aprimary excitation coil for inducing a primary magnetic field, theprimary excitation coil disposed about the panel; a plurality ofsecondary coils disposed within or proximate to the panel, the panelconfigured as a barrier between the plurality of secondary coils and oneor more biological samples, the plurality of secondary coils fordetecting a change in the magnetic field due to proximity of magneticnanoparticles or superparamagnetic nanoparticles in the sample withrespect to at least one secondary coil of the plurality of secondarycoils; and a processor communicatively coupled to the plurality ofsecondary coils, the processor for generating an image based upon thechange in magnetic field, the image representing one or more attributesof the one or more biological samples.
 2. The image sensor of claim 1,wherein the processor further determines one or more attributes of theone or more biological samples based upon the generated image.
 3. Theimage sensor of claim 1, wherein the panel comprises a glass material.4. The image sensor of claim 1, wherein the image sensor can be utilizedin a plurality of environmental settings, the plurality of environmentalsettings including at least one of a hostile environment, an indoorenvironment, or an outdoor environment.
 5. The image sensor of claim 1,wherein the image sensor is at least partially powered by a near fieldcommunications (NFC) module.
 6. The image sensor of claim 1 and furthercomprising: a mobile detection or measurement device that includes thefield image sensor and having dimensions ranging from about fourcentimeters (4 cm) by about two centimeters (2 cm) by about onemillimeter (1 mm) to about twenty centimeters (20 cm) by about fivecentimeters (5 cm) by about one centimeter (1 cm).